A B C D E F G H I J K L M N O P Q R S T U V W X Z

N

NA - Static variable in class de.jstacs.results.StorableResult

The Storable cannot be trained anyway.

name - Variable in class de.jstacs.AnnotatedEntity

The name of the entity.

NAME - Static variable in class de.jstacs.classifiers.performanceMeasures.PRCurve

The name of the performance measure return by PRCurve.getName()

NAME - Static variable in class de.jstacs.classifiers.performanceMeasures.ROCCurve

The name of the performance measure return by ROCCurve.getName()

name - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

The names of the states.

name - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState

The name of the state.

nameTemplate - Variable in class de.jstacs.parameters.ExpandableParameterSet

A template for the name of the enclosing ParameterSetContainer

NegativeDifferentiableFunction - Class in de.jstacs.algorithms.optimization

The negative function -f for a given DifferentiableFunction f.

NegativeDifferentiableFunction(DifferentiableFunction) - Constructor for class de.jstacs.algorithms.optimization.NegativeDifferentiableFunction

Creates the DifferentiableFunction f for which -f should be calculated.

NegativeFunction - Class in de.jstacs.algorithms.optimization

The negative function -f for a given Function f.

NegativeFunction(Function) - Constructor for class de.jstacs.algorithms.optimization.NegativeFunction

Creates the Function f for which -f should be calculated.

NegativeOneDimensionalFunction - Class in de.jstacs.algorithms.optimization

This class extends the class OneDimensionalFunction.

NegativeOneDimensionalFunction(OneDimensionalFunction) - Constructor for class de.jstacs.algorithms.optimization.NegativeOneDimensionalFunction

Creates the OneDimensionalFunction f for which -f should be calculated.

NewickParser - Class in de.jstacs.sequenceScores.statisticalModels.trainable.phylo.parser

This class implements a simple newick parser and allows the construction of a PhyloTree

NewickParser(BufferedReader) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.parser.NewickParser

This constructor initialize the newick parser

next() - Method in class de.jstacs.data.DataSet.ElementEnumerator

next() - Method in class de.jstacs.parameters.MultiSelectionParameter

next() - Method in interface de.jstacs.parameters.RangeIterator

Switches to the next value in the collection of values in the specified range.

next() - Method in class de.jstacs.parameters.RangeParameter

Returns true if the next element still exists and can be fetched using RangeParameter.getValue(), false otherwise.

next() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

next() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

This method steps to the next reasonable outcome if possible.

next() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator

Steps to the next combination.

next() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.SequenceIterator

Changes the internal sequence representation to the next sequence.

next(int) - Method in class de.jstacs.utils.random.RandomNumberGenerator

nextBeta(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Beta(alpha,beta) (E(X)=a/(a+b) ; Var(X)=ab/[(a+b+1)(a+b)^2])

nextBoolean() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random boolean variable

nextBoolean(double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates true with probability p

nextChiSq() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from ChiSq(1) (E(X)=1 ; Var(X)=2)

nextChiSq(int) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from ChiSq(df) (E(X)=df ; Var(X)=2*df)

nextChiSq(int, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from shifted-ChiSq(df) (E(X)=df+lambda ; Var(X)=2*df)

nextElement() - Method in class de.jstacs.data.DataSet.ElementEnumerator

nextElement() - Method in class de.jstacs.data.DataSetKMerEnumerator

nextElement() - Method in class de.jstacs.data.DiscreteSequenceEnumerator

nextElement() - Method in class de.jstacs.data.SequenceEnumeration

nextElement() - Method in class de.jstacs.io.InfixStringExtractor

nextElement() - Method in class de.jstacs.io.LimitedStringExtractor

nextElement() - Method in class de.jstacs.io.SimpleStringExtractor

nextElement() - Method in class de.jstacs.io.SparseStringExtractor

nextElement() - Method in class de.jstacs.io.StringExtractor

nextElement() - Method in class de.jstacs.io.SymbolExtractor

nextExp() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Exp(1) (E(X)=1 ; Var(X)=1)

nextExp(double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Exp(beta) (E(X)=beta ; Var(X)=beta^2)

nextExp(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from shifted-Exp(beta) (E(X)=beta+lambda ; Var(X)=beta^2)

nextGamma() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Gamma(1,1) (E(X)=1 ; Var(X)=1)

nextGamma(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Gamma(alpha,beta) (E(X)=alpha*beta ; Var(X)=alpha*beta^2)

nextGamma(double, double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from shifted-Gamma(alpha,beta) (E(X)=alpha*beta+lambda ; Var(X)=alpha*beta^2)

nextGammaLog(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

nextGaussian() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from N(0,1) (E(X)=0 ; Var(X)=1)

nextGaussian(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from N(m,s2) (E(X)=m ; Var(X)=s2)

nextInt() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates an integer between 0 and 2^32

nextInt(int) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates an integer between 0 and n-1 (inclusive)

nextPoisson(double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Poisson(lambda) (E(X)=lambda ; Var(X)=lambda)

nextPoisson() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Poisson(1) (E(X)=1 ; Var(X)=1)

nextSequence() - Method in class de.jstacs.data.bioJava.SimpleSequenceIterator

nextUniform() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from U(0,1) (E(X)=1/2 ; Var(X)=1/12)

nextUniform(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from U(a,b) (E(X)=(b-a)/2 ; Var(X)=(b-a)^2/12)

NiceScale - Class in de.jstacs.utils

Class for creating nive tick marks on axes given a minimum and maximum value.

NiceScale(double, double) - Constructor for class de.jstacs.utils.NiceScale

Creates a NiceScale object for the given minimum and maximum

NO_SMOOTHING - Static variable in enum de.jstacs.data.DinucleotideProperty

NonParsableException - Exception in de.jstacs.io

A NonParsableException is thrown if some object could not be restored (parsed) from a StringBuffer.

NonParsableException() - Constructor for exception de.jstacs.io.NonParsableException

Creates a new NonParsableException with standard error message ("StringBuffer not parsable.").

NonParsableException(String) - Constructor for exception de.jstacs.io.NonParsableException

Creates a new NonParsableException with given error message.

NoRevertHistory - Class in de.jstacs.motifDiscovery.history

This class implements a history that allows operations, that are not a priorily forbidden and do not create a configuration that has already be considered.

NoRevertHistory() - Constructor for class de.jstacs.motifDiscovery.history.NoRevertHistory

This constructor creates an instance that allows to shift shrink and expand the motif.

NoRevertHistory(boolean, boolean, boolean) - Constructor for class de.jstacs.motifDiscovery.history.NoRevertHistory

This constructor creates an instance with user specified allowed operations.

NoRevertHistory(StringBuffer) - Constructor for class de.jstacs.motifDiscovery.history.NoRevertHistory

This is the constructor for the interface Storable.

norm - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction

Indicates whether a normalization should be done or not.

norm - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This double contains the normalization constant of the instance.

Normalisation - Class in de.jstacs.utils

This class can be used for normalisation of any double array or a part of a double array.

Normalisation() - Constructor for class de.jstacs.utils.Normalisation

normalisation(double[], double) - Static method in class de.jstacs.utils.Normalisation

The method does a normalisation on d using the value v for normalisation.

normalisation(double[], double, double[], int) - Static method in class de.jstacs.utils.Normalisation

The method does a normalisation on d writing the result to dest starting at position start while d remains unchanged.

normalisation(double[], double, int, int) - Static method in class de.jstacs.utils.Normalisation

The method does a sum normalisation on d between start index start and end index end using the value v for the normalisation.

normalize(double[]) - Static method in class de.jstacs.utils.PFMComparator

This method enables the user to normalize a array containing counts.

NormalizedDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable

This class makes an unnormalized DifferentiableStatisticalModel to a normalized DifferentiableStatisticalModel.

NormalizedDiffSM(DifferentiableStatisticalModel, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM

Creates a new instance using a given DifferentiableStatisticalModel.

NormalizedDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM

This is the constructor for Storable.

NormalizedEuclideanDistance() - Constructor for class de.jstacs.utils.PFMComparator.NormalizedEuclideanDistance

normalizeParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Normalizes the parameter values to the corresponding log-probabilities.

normalizeParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

Normalizes all parameters to log-probabilities.

normalizePlugInParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Starts the normalization of the plug-in parameters to the logarithm of the MAP-estimates.

NOT_TRAINED_VALUE - Static variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

This value should be used in ScoreClassifier.getLastScore() if the classifier is not trained.

NotInstantiableException(String) - Constructor for exception de.jstacs.io.ParameterSetParser.NotInstantiableException

Creates a new instance of a ParameterSetParser.NotInstantiableException with a given error message.

NotTrainedException - Exception in de.jstacs

A NotTrainedException is thrown if the user tries to use an untrained model.

NotTrainedException() - Constructor for exception de.jstacs.NotTrainedException

Creates a new NotTrainedException with standard error message ("The model is not trained yet.

NotTrainedException(String) - Constructor for exception de.jstacs.NotTrainedException

Creates a new NotTrainedException with given error message.

nsf - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM

The internally used DifferentiableStatisticalModel.

NullProgressUpdater - Class in de.jstacs.utils

This class implements a ProgressUpdater doing nothing but forces a crossvalidation that is used with an instance of this class to continue to its end.

NullSequenceAnnotationParser - Class in de.jstacs.data.sequences.annotation

This SequenceAnnotationParser returns always null as SequenceAnnotation.

numberOfParameters - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM

The number of parameters of this HMM

numberOfSummands - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Helper variable = only for internal use.

NumberValidator<E extends Comparable<? extends Number>> - Class in de.jstacs.parameters.validation

Class that validates all subclasses of Number that implement Comparable (e.g.

NumberValidator(E, E) - Constructor for class de.jstacs.parameters.validation.NumberValidator

Constructs a NumberValidator for a given upper and lower bound.

NumberValidator(StringBuffer) - Constructor for class de.jstacs.parameters.validation.NumberValidator

The standard constructor for the interface Storable.

NumericalDifferentiableFunction - Class in de.jstacs.algorithms.optimization

This class is the framework for any numerical differentiable function .

NumericalDifferentiableFunction(Function, double) - Constructor for class de.jstacs.algorithms.optimization.NumericalDifferentiableFunction

Sets the function and value for epsilon for this NumericalDifferentiableFunction.

NumericalHMMTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

This class implements an ParameterSet for numerical training of an AbstractHMM.

NumericalHMMTrainingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet

This is the empty constructor that can be used to fill the parameters after creation.

NumericalHMMTrainingParameterSet(int, AbstractTerminationCondition, int, byte, double, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet

This constructor can be used to create an instance with specified parameters.

NumericalHMMTrainingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet

The standard constructor for the interface Storable.

NumericalPerformanceMeasure - Interface in de.jstacs.classifiers.performanceMeasures

This interface indicates that a Performance measure returns numerical results.

NumericalPerformanceMeasureParameterSet - Class in de.jstacs.classifiers.performanceMeasures

This class implements a container for NumericalPerformanceMeasures that can be used, for instance, in an repeated assessment, (cf.

NumericalPerformanceMeasureParameterSet(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.NumericalPerformanceMeasureParameterSet

The standard constructor for the interface Storable.

NumericalPerformanceMeasureParameterSet(int) - Constructor for class de.jstacs.classifiers.performanceMeasures.NumericalPerformanceMeasureParameterSet

Constructs a new NumericalPerformanceMeasureParameterSet that can be used for classifiers that handle the given number of classes.

NumericalPerformanceMeasureParameterSet(NumericalPerformanceMeasure...) - Constructor for class de.jstacs.classifiers.performanceMeasures.NumericalPerformanceMeasureParameterSet

Constructs a new NumericalPerformanceMeasureParameterSet with the given performance measures.

NumericalResult - Class in de.jstacs.results

Class for numerical Result values.

NumericalResult(StringBuffer) - Constructor for class de.jstacs.results.NumericalResult

The standard constructor for the interface Storable.

NumericalResult(DataType, String, String, Comparable) - Constructor for class de.jstacs.results.NumericalResult

Creates a NumericalResult of a primitive numerical data type.

NumericalResult(String, String, double) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the primitive type double.

NumericalResult(String, String, int) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the primitive type int.

NumericalResult(String, String, Integer) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the type Integer.

NumericalResult(String, String, long) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the primitive type long.

NumericalResultSet - Class in de.jstacs.results

Class for a set of numerical result values, which are all of the type NumericalResult.

NumericalResultSet(NumericalResult) - Constructor for class de.jstacs.results.NumericalResultSet

Constructs a NumericalResultSet containing one NumericalResult.

NumericalResultSet(NumericalResult[]...) - Constructor for class de.jstacs.results.NumericalResultSet

Constructs a NumericalResultSet from some arrays of NumericalResults.

NumericalResultSet(LinkedList<? extends NumericalResult>) - Constructor for class de.jstacs.results.NumericalResultSet

Constructs a NumericalResultSet from a LinkedList of NumericalResults.

NumericalResultSet(StringBuffer) - Constructor for class de.jstacs.results.NumericalResultSet

The standard constructor for the interface Storable.

numFreePars - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

The number of free parameters.

nums - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

Used internally.

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